ArticlePloS one2018
Approaches to variant discovery for conifer transcriptome sequencing.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Pinus radiata genome reveals a downward demographic trajectory and opportunities for genomics-assisted breeding.G3 (Bethesda, Md.) · 2025Article
- High density linkage maps, genetic architecture, and genomic prediction of growth and wood properties in Pinus radiata.BMC genomics · 2022Article
- Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection.International journal of molecular sciences · 2022Review
- Chasing genetic correlation breakers to stimulate population resilience to climate change.Scientific reports · 2022Article
- Analysis of the transcriptome of the needles and bark of Pinus radiata induced by bark stripping and methyl jasmonate.BMC genomics · 2022Article
- Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth inFrontiers in plant science · 2021Article
- Effect of trait's expression level on single-step genomic evaluation of resistance to Dothistroma needle blight.BMC plant biology · 2020Article
- Marker Selection in Multivariate Genomic Prediction Improves Accuracy of Low Heritability Traits.Frontiers in genetics · 2020Article
- Reduced Virulence of an Introduced Forest Pathogen over 50 Years.Microorganisms · 2019Article
- A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata.PloS one · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a wide diversity of bioinformatic tools available for the assembly of next generation sequence and subsequence variant calling to identify genetic markers at scale. Integration of genomics tools such as genomic selection, association studies, pedigree analysis and analysis of genetic diversity, into operational breeding is a goal for New Zealand's most widely planted exotic tree species, Pinus radiata. In the absence of full reference genomes for large megagenomes such as in conifers, RNA sequencing in a range of genotypes and tissue types, offers a rich source of genetic markers for downstream application. We compared nine different assembler and variant calling software combinations in a single transcriptomic library and found that Single Nucleotide Polymorphism (SNPs) discovery could vary by as much as an order of magnitude (8,061 SNPs up to 86,815 SNPs). The assembler with the best realignment of the packages trialled, Trinity, in combination with several variant callers was then applied to a much larger multi-genotype, multi-tissue transcriptome and identified 683,135 in silico SNPs across a predicted 449,951 exons when mapped to the Pinus taeda ver 1.01e reference.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.